Instructions to use eadx/deepseek-v4-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use eadx/deepseek-v4-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="eadx/deepseek-v4-gguf", filename="DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use eadx/deepseek-v4-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf eadx/deepseek-v4-gguf:F32 # Run inference directly in the terminal: llama-cli -hf eadx/deepseek-v4-gguf:F32
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf eadx/deepseek-v4-gguf:F32 # Run inference directly in the terminal: llama-cli -hf eadx/deepseek-v4-gguf:F32
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf eadx/deepseek-v4-gguf:F32 # Run inference directly in the terminal: ./llama-cli -hf eadx/deepseek-v4-gguf:F32
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf eadx/deepseek-v4-gguf:F32 # Run inference directly in the terminal: ./build/bin/llama-cli -hf eadx/deepseek-v4-gguf:F32
Use Docker
docker model run hf.co/eadx/deepseek-v4-gguf:F32
- LM Studio
- Jan
- Ollama
How to use eadx/deepseek-v4-gguf with Ollama:
ollama run hf.co/eadx/deepseek-v4-gguf:F32
- Unsloth Studio
How to use eadx/deepseek-v4-gguf with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for eadx/deepseek-v4-gguf to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for eadx/deepseek-v4-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for eadx/deepseek-v4-gguf to start chatting
- Pi
How to use eadx/deepseek-v4-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf eadx/deepseek-v4-gguf:F32
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "eadx/deepseek-v4-gguf:F32" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use eadx/deepseek-v4-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf eadx/deepseek-v4-gguf:F32
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default eadx/deepseek-v4-gguf:F32
Run Hermes
hermes
- Docker Model Runner
How to use eadx/deepseek-v4-gguf with Docker Model Runner:
docker model run hf.co/eadx/deepseek-v4-gguf:F32
- Lemonade
How to use eadx/deepseek-v4-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull eadx/deepseek-v4-gguf:F32
Run and chat with the model
lemonade run user.deepseek-v4-gguf-F32
List all available models
lemonade list
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This quants are specific for the DS4 inference engine. They may work with other inference engines or not (they should, but not the MTP model which requires a specific loader). https://github.com/antirez/ds4
license: mit
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# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="eadx/deepseek-v4-gguf", filename="", )